const std = @import("std");
const driver_manager = @import("driver_manager.zig");
const api = @import("api.zig");

// BPU驱动数据结构
const BpuDriverData = struct {
    // 驱动私有数据
    allocator: std.mem.Allocator,
    device_count: u32,
    initialized: bool,
};

// BPU设备数据结构
const BpuDeviceData = struct {
    device_id: u64,
    network_loaded: bool,
    current_network_id: u32,
    operation_status: u32,
    // 其他BPU设备相关字段
};

// BPU驱动命令
pub const BPU_IOCTL_LOAD_NETWORK = 0x401;
pub const BPU_IOCTL_UNLOAD_NETWORK = 0x402;
pub const BPU_IOCTL_EXECUTE_INFERENCE = 0x403;
pub const BPU_IOCTL_GET_STATUS = 0x404;
pub const BPU_IOCTL_SET_CONFIG = 0x405;

// BPU神经网络信息
const BpuNetworkInfo = struct {
    network_id: u32,
    network_path: [256]u8,
    layer_count: u32,
    input_nodes: u32,
    output_nodes: u32,
    // 其他网络相关信息
};

// BPU推理请求
const BpuInferenceRequest = struct {
    network_id: u32,
    input_buffers: [16]u64, // 物理地址
    output_buffers: [16]u64, // 物理地址
    input_sizes: [16]u64,
    output_sizes: [16]u64,
    node_count: u32,
    enable_profiling: bool,
};

// BPU设备状态
const BpuStatus = struct {
    device_id: u64,
    is_busy: bool,
    loaded_networks: u32,
    memory_usage: u64,
    temperature: u32,
    neuron_usage: u32, // 神经元使用率 (%)
    synapse_usage: u32, // 突触使用率 (%)
};

// BPU配置参数
const BpuConfig = struct {
    frequency: u32, // MHz
    power_mode: u8, // 0: 省电, 1: 平衡, 2: 高性能
    memory_limit: u64, // 字节
    quantization_mode: u8, // 0: 8位, 1: 16位, 2: 32位
    enable_pruning: bool,
};

// 初始化驱动
fn init_driver(allocator: std.mem.Allocator, driver_data: *anyopaque) bool {
    std.log.info("BPU driver initialized");
    
    // 分配驱动数据
    const bpu_data = allocator.create(BpuDriverData) catch {
        std.log.err("Failed to allocate BPU driver data");
        return false;
    };
    
    bpu_data.* = BpuDriverData{
        .allocator = allocator,
        .device_count = 0,
        .initialized = true,
    };
    
    // 存储驱动数据
    @atomicStore(*anyopaque, driver_data, bpu_data, .Release);
    return true;
}

// 清理驱动
fn deinit_driver(driver_data: *anyopaque) void {
    const bpu_data = @ptrCast(*BpuDriverData, @alignCast(@alignOf(BpuDriverData), driver_data));
    std.log.info("BPU driver deinitialized");
    bpu_data.allocator.destroy(bpu_data);
}

// 探测设备
fn probe_device(device_info: *driver_manager.DeviceInfo) bool {
    // 检查是否为BPU设备
    std.log.info("BPU driver probing device: VID={x}, PID={x}", .{device_info.vendor_id, device_info.device_id});
    
    // 这里我们假设BPU设备的类ID范围是0x0B0000到0x0BFFFF
    if (device_info.class_id >= 0x0B0000 and device_info.class_id <= 0x0BFFFF) {
        std.log.info("BPU device matched");
        return true;
    }
    
    return false;
}

// 移除设备
fn remove_device(device_id: u64) void {
    std.log.info("BPU driver removing device: {d}", .{device_id});
    // 这里应该清理与该设备相关的所有资源
}

// IO控制
fn ioctl_device(device_id: u64, cmd: u32, data: *anyopaque, size: u64) isize {
    std.log.info("BPU driver IOCTL: device={d}, cmd={x}, size={d}", .{device_id, cmd, size});
    
    switch (cmd) {
        BPU_IOCTL_LOAD_NETWORK => {
            if (size < @sizeOf(BpuNetworkInfo)) {
                return -1; // 缓冲区太小
            }
            
            const network_info = @ptrCast(*BpuNetworkInfo, @alignCast(@alignOf(BpuNetworkInfo), data));
            std.log.info("Loading neural network: ID={d}, Path={s}", .{network_info.network_id, &network_info.network_path});
            std.log.info("Layers: {d}, Input nodes: {d}, Output nodes: {d}", .{network_info.layer_count, network_info.input_nodes, network_info.output_nodes});
            
            // 模拟网络加载过程
            std.log.info("Neural network loaded successfully");
            return 0;
        },
        
        BPU_IOCTL_UNLOAD_NETWORK => {
            if (size < @sizeOf(u32)) {
                return -1; // 缓冲区太小
            }
            
            const network_id = @ptrCast(*u32, @alignCast(@alignOf(u32), data));
            std.log.info("Unloading neural network: ID={d}", .{network_id.*});
            
            // 模拟网络卸载过程
            std.log.info("Neural network unloaded successfully");
            return 0;
        },
        
        BPU_IOCTL_EXECUTE_INFERENCE => {
            if (size < @sizeOf(BpuInferenceRequest)) {
                return -1; // 缓冲区太小
            }
            
            const request = @ptrCast(*BpuInferenceRequest, @alignCast(@alignOf(BpuInferenceRequest), data));
            std.log.info("Executing neural inference: Network ID={d}", .{request.network_id});
            std.log.info("Node count: {d}, Profiling: {}", .{request.node_count, request.enable_profiling});
            
            // 模拟推理执行
            std.log.info("Neural inference completed successfully");
            return @sizeOf(u64); // 返回结果大小
        },
        
        BPU_IOCTL_GET_STATUS => {
            if (size < @sizeOf(BpuStatus)) {
                return -1; // 缓冲区太小
            }
            
            const status = @ptrCast(*BpuStatus, @alignCast(@alignOf(BpuStatus), data));
            status.device_id = device_id;
            status.is_busy = false;
            status.loaded_networks = 1;
            status.memory_usage = 1024 * 1024 * 384; // 假设使用了384MB内存
            status.temperature = 67; // 假设温度为67°C
            status.neuron_usage = 45; // 假设神经元使用率为45%
            status.synapse_usage = 60; // 假设突触使用率为60%
            
            return @sizeOf(BpuStatus);
        },
        
        BPU_IOCTL_SET_CONFIG => {
            if (size < @sizeOf(BpuConfig)) {
                return -1; // 缓冲区太小
            }
            
            const config = @ptrCast(*BpuConfig, @alignCast(@alignOf(BpuConfig), data));
            std.log.info("Setting BPU config: Freq={d}MHz, PowerMode={d}, MemLimit={d}MB, QuantMode={d}, Pruning={}", 
                .{config.frequency, config.power_mode, config.memory_limit / (1024 * 1024), config.quantization_mode, config.enable_pruning});
            
            // 模拟配置设置
            std.log.info("BPU config updated successfully");
            return 0;
        },
        
        else => {
            std.log.info("Unknown BPU IOCTL command");
            return -1; // 未知命令
        },
    }
}

// BPU驱动接口
pub const bpu_driver_interface = driver_manager.DriverInterface{
    .name = "bpu_driver",
    .description = "Brain Processing Unit driver",
    .version = 1,
    .init = init_driver,
    .deinit = deinit_driver,
    .probe = probe_device,
    .remove = remove_device,
    .ioctl = ioctl_device,
};

// 导出驱动接口
export fn bpu_driver_get_interface() *driver_manager.DriverInterface {
    return &bpu_driver_interface;
}